Application of markerless image-based arm tracking to robot-manipulator teleoperation
Bibliographic record
Abstract
In robot teleoperation, contacting mechanical devices and sensors have been commonly used to track operator hand and arm motion. While camera-based tracking has the benefit of being non-contacting, markerless camera-based human tracking offers a further advantage of not requiring markers and thus avoiding marker occlusion. This paper presents an application of markerless image-based arm tracking to real-time teleoperation of a robot manipulator. The markerless tracking is carried out by processing images from two calibrated cameras in real-time, to estimate the positions of the joint centres of the wrist and elbow in three dimensions (3D), and to compute the 3D positions of the index finger and thumb in order to estimate the hand orientation. These are used to determine the position and orientation of the endeffector of a robot-manipulator in real-time teleoperation. Markerless tracking for teleoperation was demonstrated for pick-and-place tasks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".